Model overview
A decensored version of Prism ML's Ternary-Bonsai-2-27B, with an OT-Ridge LoRA baked into the ternary weights. It succeeds Ternary-Bonsai-2-27B-Uncensored-Heretic-GGUF (v1). - **Thinking that finishes**: responses with no final answer within 4,096 tokens (thinking on) 22% → 9%; with greedy decoding 70% → 16%. - **Smaller capability cost**: MMLU −1.63 → −0.66 points against the original model; HumanEval −1.83 → −0.61 points (not significant). Refusals: keyword matching on the 100 Japanese harmful prompts above (greedy, thinking off). KL divergence: first-token KL on 100 held-out Japanese prompts (Magpie-Tanuki train[400:500]); v1's card used another prompt set, so the two KL values are not comparable.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。